The amount of data generated globally will reach 463 exabytes every day by 2025. Aside from controlling and processing that data, tapping into and turning it into a business asset is the biggest challenge enterprises face.

Thinking data-first in business means thinking laterally about how you can integrate data into your operations. How can the data you collect, process, and control yield value to your organisation at every level?

Putting trust in data

The critical difference between a data-first and data-informed enterprise is decisions are made with data as the key driver rather than instinct. Human instinct still exists, but data is the primary commodity in decision-making.

This enables automation and artificial intelligence to streamline operations, with technology making operational decisions to free up executive time. However, this requires authoritative data sources and verification to instil trust.

Decisions made with data drive positive business outcomes, but a lack of trust in data can sour the relationship. Breaking down silos, empowering employees with access to data, verifying data sources, and investing in new data management tools can instil confidence in data to transform your business into a data-first one.

Thinking data-first

Lateral thinking behind how you organise, administrate, and govern big data is what it means to take a data-first approach. It ultimately requires you to trust data to the point where you can pin business strategies on it.

Enterprises’ most significant challenge is figuring out how to access, filter, sort, and organise data, so it makes sense. Additionally, businesses struggle to quantify data and refine data sources to yield high-quality information.

Data isn’t just a tool to help guide business strategy – it’s the only tool because of its sheer volume. Here are eight questions you need to answer:

  • How siloed is your data?
  • What does your technology stack look like?
  • How do you control and process data?
  • Can you quantify and understand the data?
  • Do you know how to leverage data?
  • Is your data strategy benefitting your business?
  • Is innovation a goal or a hurdle?
  • Does your existing data strategy give you a competitive edge?

The last question – does your existing data strategy give you a competitive edge? – will define your next steps; data is your business’s most significant asset to make good decisions around operational models and drive revenue. If you don’t leverage data, you can bet your house that your competitors will leapfrog you.

10 principles to get the most from your data-driven transformation

Data-driven transformation’s primary goal is ensuring the systems that connect data producers and consumers are secure and easy to deploy.However, the biggest challenge is finding and leveraging data for operational and competitive advantages. Almost any business can adopt the systems and technology to handle and process data, but not many can evaluate it.

To ensure your enterprise stays on the right track, here are ten principles to get the most out of your data-driven transformation:

  1. Understand the value in data

What is data worth to your enterprise? Before jumping into transformation, you must seek clarity on how valuable data is as an asset. The value in data will drive your data strategy and how it integrates into your operational models.

  1. Determine what makes data valuable

Is it the volume, quality, rarity, uniqueness, or source of data that makes it valuable to your enterprise? Developing a value architecture for tying value to data will enable you to comprehensively determine what makes data valuable.

  1. Figure out your current data position

Where are you in your data journey? Conduct an audit to find out how data is treated across your organisation. Key focus points are governance, management, security, data architectures, consumption and distribution, data knowledge, and data monetisation.

  1. Deal with data from various sources

Where is your data coming from? We can guarantee there are multiple sources. You need to figure out where data comes from to validate sources and implement a data strategy that designates paths that datasets must follow.

  1. C-suite strategic commitment

Data-driven transformation is a no-go when executives aren’t on board, but they must get on the ship. Otherwise, all that data won’t convert into business value – it will be a dead asset weighing down your enterprise.

  1. Assure trust in data

Trust in data starts with the systems and processes that collect it and the sources. As data passes through architecture, it must be securely held and encrypted so that no tampering can occur and there is a paper trail for verification.

  1. Seize upon metadata opportunities

Data that provides information about other data (metadata) is as critical to your enterprise as cloud computing. Metadata provides context and clarity to data, helping you find value in it and determine how to manage it.

  1. Instil data-driven culture

It’s all-well-and-good C-suite executives and IT leaders getting behind your enterprise’s data-driven transformation. However, lower-level cultural barriers like silos, complex data sharing policies and data hoarders will stunt your data-driven transformation.

  1. Security is a top priorityData security should be your top priority when collecting and processing data. Your security policies should envelop IT architecture, security practices and employee awareness, ensuring tight security and trust throughout the entire stack.
  2. Embrace automation and artificial intelligence

Automating manual processes, lightening workloads and letting ‘the machine’ run things shouldn’t scare you – it should excite you. Fully automated data pipelines offer substantial efficiency gains and extract the true value from data on autopilot.

We can help you transform your business with data-first thinking. Take the next step by speaking with our experts about modernising your data infrastructure.